Hunt Institute for Botanical Documentation
A Research Division of Carnegie Mellon University

Hunt Institute Archives Text Discovery Platform

Search a large and growing portion of our online collections, including handwritten documents.
PROTOTYPE

This prototype uses state-of-the-art artificial intelligence, including a vision-language model (VLM) capable of reading handwritten documents as well as typed and printed text, to create searchable transcriptions of digitized materials in the Hunt Institute Archives. This makes it possible to search the textual contents of individual pages, including material that may not be described in the archival catalog.

Use Keyword search for specific words, names, dates, scientific names, or phrases. Try Semantic search (experimental) to describe a topic, question, or kind of material when you do not know the exact wording used in the documents.

About the AI-generated transcriptions

The transcriptions are generated automatically from page images and may contain errors, especially with difficult handwriting, unusual names, multiple languages, image-quality problems, or complex layouts. They are intended primarily as a discovery aid rather than authoritative transcriptions.

Each result provides the generated transcription and links to the original digitized material and associated archival description so that readings can be checked against the source. The transcription workflow uses AI models run locally by the Hunt Institute.

About Keyword and Semantic search

Keyword search is the default and matches the wording in the transcriptions. Results contain all your terms. Use quotes for an exact phrase. Substring matching is supported, so aceae can find plant-family names ending in -aceae.

Semantic search (experimental) is useful when you know what kind of material you are looking for but do not know the words used in the documents. It ranks transcribed passages by similarity of meaning, so relevant results may not contain the exact words in your query.

Semantic queries can be broad research topics, descriptions of activities or relationships, or natural-language questions. For example:

Semantic search is not a chatbot: a question is used as a search query, and the system returns archival passages that appear conceptually related to it rather than generating an answer or summary. Short descriptions and ordinary research questions generally work better than lists of disconnected keywords. Quotation marks have no special meaning in Semantic mode. Cross-language matching may work in some cases, but it should not be treated as translation.

Keyword and Semantic search are complementary. Keyword search lets you require particular wording; Semantic search can surface differently worded passages about the same subject. Depending on the research question, trying both can reveal different useful material.

Open a result: use the prominent page-and-transcription link to see the metadata, PDF, and full transcription. Keyword-search terms are highlighted in the transcription.

Archives Collections Database (ArchivesSpace): the Collection, Item/Folder, and Digital Object links open the corresponding archival records. Collection-level dates describe the collection as a whole, not necessarily the specific item or page.

If a PDF does not load: on the detail page, use the Digital Object link, click “Go to file” in ArchivesSpace, and navigate to the page number shown here.

Current limitations
  • Automated transcriptions can contain missing or incorrect text or unintended repetition. Difficult handwriting, image quality, unusual layouts, and multiple languages can reduce accuracy. Always consult the original page image when an exact reading matters.
  • Semantic search remains experimental. Its rankings are an additional discovery aid, not a complete or definitive set of relevant results, and highly ranked pages can sometimes be only broadly related.
  • This is an active prototype. Search coverage, transcriptions, functionality, and the interface may continue to change as additional archival material is processed and the system is improved.

← Back to results

Page 104 · DO #1244 · 53_Arber_AN10r

Collection
Agnes Robertson Arber (1879–1960) papers
Item/Folder
Notebook An 10 -- Herbal Critical Later notes (post 1912) H. C. 3, 1928–1936, n.d.
Digital Object
DO #1244, page 104
Collection-level dates
1886–1985
Open PDF at page 104 ↗

Page transcription

Camus J (1895)
p314 A letter from Tizoli he did not publish was an
ordinance limiting the sale of 50 years & was intended to
commemorate his friend, so that he had great
influence on 200 years of botany.

p263
No expense / expenses / expenses / expenses has been
suggested as a reason why herbaria were not made.
But in reality there is no such plants minus a small
number of species. "Now, it must be remembered,
that the ancients have not composed herbiers, but
simply because no one has imagined that anyone could
collect them. The idea did not come to botanists until
a late period) to Darwinism, a long time ago
proper how became relatively cheap - common

p276
The two things which arrested the development of botany
apart from medicine were collections / plant drawings for
nature. Collections I drew plants

On Jean Berendtchon's Plan-Drawings (1588) : Journal
de Botanique IV Paris 1894
Andrea Amaglio 1615. a collection well
drawn plants & the doctor Benedicto Rino. In
Bibliothèque S. Marc, Venice.

In 16th century explorers were content to take back
seeds / drawings / plants when they observed
Falconer to describe / Assates is very much a
herbarium, stunts June r. botanical book [3th to last]
Falconer was the first (only) who made a
collection (using means) of industrial plants before the
Etabl d'Est 1540-1550
Falconer was to Etabl d'Est 1540-1550
The Narratives & Anct's descriptions
p295. The Narratives & Anct's descriptions